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Significant association between sulfate-reducing bacteria and uranium-reducing microbial communities as revealed by a combined massively parallel sequencing-indicator species approach.

ABSTRACT: Massively parallel sequencing has provided a more affordable and high-throughput method to study microbial communities, although it has mostly been used in an exploratory fashion. We combined pyrosequencing with a strict indicator species statistical analysis to test if bacteria specifically responded to ethanol injection that successfully promoted dissimilatory uranium(VI) reduction in the subsurface of a uranium contamination plume at the Oak Ridge Field Research Center in Tennessee. Remediation was achieved with a hydraulic flow control consisting of an inner loop, where ethanol was injected, and an outer loop for flow-field protection. This strategy reduced uranium concentrations in groundwater to levels below 0.126 ?M and created geochemical gradients in electron donors from the inner-loop injection well toward the outer loop and downgradient flow path. Our analysis with 15 sediment samples from the entire test area found significant indicator species that showed a high degree of adaptation to the three different hydrochemical-created conditions. Castellaniella and Rhodanobacter characterized areas with low pH, heavy metals, and low bioactivity, while sulfate-, Fe(III)-, and U(VI)-reducing bacteria (Desulfovibrio, Anaeromyxobacter, and Desulfosporosinus) were indicators of areas where U(VI) reduction occurred. The abundance of these bacteria, as well as the Fe(III) and U(VI) reducer Geobacter, correlated with the hydraulic connectivity to the substrate injection site, suggesting that the selected populations were a direct response to electron donor addition by the groundwater flow path. A false-discovery-rate approach was implemented to discard false-positive results by chance, given the large amount of data compared.

SUBMITTER: Cardenas E

PROVIDER: S-EPMC2953039 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

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Significant association between sulfate-reducing bacteria and uranium-reducing microbial communities as revealed by a combined massively parallel sequencing-indicator species approach.

Cardenas Erick E Wu Wei-Min WM Leigh Mary Beth MB Carley Jack J Carroll Sue S Gentry Terry T Luo Jian J Watson David D Gu Baohua B Ginder-Vogel Matthew M Kitanidis Peter K PK Jardine Philip M PM Zhou Jizhong J Criddle Craig S CS Marsh Terence L TL Tiedje James M JM

Applied and environmental microbiology 20100820 20

Massively parallel sequencing has provided a more affordable and high-throughput method to study microbial communities, although it has mostly been used in an exploratory fashion. We combined pyrosequencing with a strict indicator species statistical analysis to test if bacteria specifically responded to ethanol injection that successfully promoted dissimilatory uranium(VI) reduction in the subsurface of a uranium contamination plume at the Oak Ridge Field Research Center in Tennessee. Remediati ...[more]

PMID: 20729318

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Project description:Sulfate-reducing bacteria (SRBs) are one of the main sources of biogenic H2S generation in oil reservoirs. Excess H2S production in these systems leads to oil biosouring, which causes operational risks and health hazards and can increase the cost of refining crude oil. Nitrate salts are often added to the system to suppress sulfidogenesis. Because SRB populations can persist in biofilms even after nitrate treatment, identifying shifts in the sessile community is crucial for successful mitigation. However, sampling the sessile community is hampered by its inaccessibility. Here, we use the results of a long-term (148 days) ex situ experiment to identify particular sessile community members from observations of the sample waste stream. Microbial community structure was determined for 731 samples across 20 bioreactors using 16S rRNA gene sequencing. By associating microbial community structure with specific steps in the mitigation process, we could distinguish between taxa associated with H2S production and mitigation. After initiation of nitrate treatment, certain SRB populations increased in the planktonic community during critical time points, indicating the dissociation of SRBs from the biofilm. Predicted relative abundances of the dissimilatory sulfate reduction pathway also increased during the critical time points. Here, by analyzing the planktonic community structure, we describe a general method that uses high-throughput amplicon sequencing, metabolic inferences, and cell abundance data to identify successful biofilm mitigation. We anticipate that our approach is also applicable to other systems where biofilms must be mitigated but cannot be sampled easily. IMPORTANCE Microbial biofilms are commonly present in many industrial processes and can negatively impact performance and safety. Within the oil industry, subterranean biofilms cause biosouring with implications for oil quality, cost, occupational health, and the environment. Because these biofilms cannot be sampled directly, methods are needed to indirectly assess the success of mitigation measures. This study demonstrates how the planktonic microbial community can be used to assess the dissociation of sulfate-reducing bacterium (SRB)-containing biofilms. We found that an increase in the abundance of a specific SRB population in the effluent after nitrate treatment can be used as a potential indicator for the successful mitigation of biofilm-forming SRBs. Moreover, a method for determining critical time points for detecting potential indicators is suggested. This study expands our knowledge of improving mitigation strategies for biosouring and could have broader implications in other systems where biofilms lead to adverse consequences.

Dataset Information

Significant association between sulfate-reducing bacteria and uranium-reducing microbial communities as revealed by a combined massively parallel sequencing-indicator species approach.

Publications

Significant association between sulfate-reducing bacteria and uranium-reducing microbial communities as revealed by a combined massively parallel sequencing-indicator species approach.

Similar Datasets

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